Title :
An improved social spider algorithm for the Flexible Job-Shop Scheduling Problem
Author :
Yao Wang; LinBo Zhu; Jiwen Wang; Jianfeng Qiu
Author_Institution :
School of Computer Science and Technology, Anhui University, China
Abstract :
In this paper, we propose a novel swarm algorithm, called social spider algorithm (SSA), to solve the Flexible Job-Shop Scheduling Problem (FJSP). The SSA algorithm stresses the difference between the two different search agents (spiders): males and females [19]. Some strategies are utilized to generate the initial individual in order to ensure certain quality and diversity, such as global search (GS) and local search (LS) and so on. Moreover, instead of the original SSA algorithm, the improved SSA is combined with the selection, crossover and mutation operation to enhance the performance. The computational result shows that the proposed algorithm produces better results than other authors´ algorithms [23].
Keywords :
Support vector machines
Conference_Titel :
Estimation, Detection and Information Fusion (ICEDIF), 2015 International Conference on
DOI :
10.1109/ICEDIF.2015.7280181